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NAO-Teach: helping kids to learn societal and theoretical knowledge with friendly human-robot interaction

10.11591/ijeecs.v17.i3.pp1657-1664
Ahmad Hoirul Basori
Robotic technology has affected the education field, and even early education involves robot to attract Kids. Technical education is the notion of giving students knowledge of robots and technology. The main contribution of our research is to provide an interactive way of learning for kids through play and fun method. Two approaches proposed here: first, we provide an interactive game by touching robots body parts to teach kids how they were practising their motoric nerve and the listening to the instruction. In this game, kids asked to find some robot parts such as right hand, or left hand, where it equipped with a tactile sensor. The game difficulty can be increased by setting up the time limit for the answer and make kids touch the body parts of the robot very fast. The second learning method is practising number counting and pronunciation with NAO Robots. The robots will do computer vision processing to analyse and pronounce the kids handwriting with an artificial neural network. The result of implementation has obtained more than 75% success rate on recognition part with loss es than 0.6. The system received strong appreciation from kids and their parent, while  This research believed able to attract kids to study in interactive and fun ways.
Volume: 17
Issue: 3
Page: 1657-1664
Publish at: 2020-03-01

Quality of school life in Turkey, Finland and South Korea

10.11591/ijere.v9i1.20522
Ayşe Elitok Kesici , Veysel Karani Ceylan
This study was aimed to compare the major studies conducted on the quality of school life in Turkey, Finland and South Korea. The study focuses on which dimensions of quality of school life research in these three countries were examined, their participants, school levels and research methods. This research is in the literature review model. In this context, data were obtained by scanning the related books, theses and articles. In the research, document analysis technique of qualitative research method was used to collect data. Based on the research findings, it is seen that research studies have been conducted in Finland to establish the theoretical framework for conceptualization of the subject. Qualitative, quantitative and mixed methods were used in research studies conducted in South Korea. In the research conducted in three countries, the concept of self, bullying, implicit program, gender, socio-economic level, classmate, teacher and family support, self-efficacy, music, living environment, self and teacher-learner relationship have been determined to affect quality of school life. In the research studies conducted in Turkey, levels of quality of school life were detected, whereas in the research studies conducted in South Korea, the importance of traditional values of Confucius doctrine were focused on.
Volume: 9
Issue: 1
Page: 100-108
Publish at: 2020-03-01

The opinions of students, professors and practice teachers on the teaching practice course

10.11591/ijere.v9i1.20363
Esra Töre
The goal of this study was the evaluation of the teaching practice course in the Psychological Counseling and Guidance (PCG) department by students, professors and practice teachers. It was a pneumology study designed with qualitative research method. The study group consists of seven students, five professors and five practice teachers from 3 different schools and 3 different universities in İstanbul. Study data were analyzed with content analysis. It was found that the communication and collaboration between the professors and practice teachers of the teaching practice course were low, and the applications within the scope of the course were inadequate. Additionally, the study has revealed that it is necessary to inform the practice teachers about the previous courses and internships the students have taken, to ensure the attendance of students to full-day practice courses on different days and that a detailed teaching practice course guide is prepared. This study is thought to benefit the literature in the sense that it shows how PCG teaching practice course differs from other teaching practice courses, in addition to suggestions to the decision makers and practitioners for improving the course.
Volume: 9
Issue: 1
Page: 10-20
Publish at: 2020-03-01

Two state-of-the-arts current-mode ternary full adders based on CNTFET Technology

10.11591/ijres.v9.i1.pp19-27
Mona Moradi
Adder core respecting to its various applications in VLSI circuits and systems is considered as the most critical building block in microprocessors, digital signal processors and arithmetic operations. Novel designs of a low power and complexity Current Mode 1-bit Full Adder cell based on CNTFET technology has been presented in this paper. Three major parts construct their structures; 1) the first part that converts current to voltage; 2) threshold detectors (TD); and 3) parallel paths to convey the output currents flow. Adjusting threshold voltages which are significant factor for setting threshold detectors switching point has been achieved by means of CNTFET technology. It would bring significant improvements in adjusting threshold voltages, regarding to its unique characterizations. Simple design, less transistor counts and static power dissipation and better performance comparing previous designs could be considered as some advantages of the novel designs.
Volume: 9
Issue: 1
Page: 19-27
Publish at: 2020-03-01

A compact model of transconductance and drain conductance for DMG-GC-DOT cylindrical gate MOSFET

10.11591/ijres.v9.i1.pp34-41
Hind Jaafar , Abdellah Aouaj , Benjamin Iñiguez , Ahmed Bouziane
A compact model for dual-material gate graded-channel and dual-oxide thickness with two dielectric constant different cylindrical gate (DMG-GC-DOTTDCD) MOSFET was investigated in terms of transconductance, drain conductance and capacitance. Short channel effects are modeled with simple expressions, and incorporated into the core of the model (at the drain current). The design effectiveness of DMG-GC-DOTTDCD was monitored in comparing with the DMG-GC-DOT transistor, the effect of variations of technology parameters, was presented in terms of gate polarization and drain polarization. The results indicate that the DMG-GC-DOTTDCD devices have characteristics higher than the DMG-GC-DOT MOSFET. To validate the proposed model, we used the results obtained from the simulation of the device with the SILVACO-ATLAS-TCAD software.
Volume: 9
Issue: 1
Page: 34-41
Publish at: 2020-03-01

Filtering and acquisition of serial data frames using xilinx system generator

10.11591/ijres.v9.i1.pp1-11
Adrián Gonzalo Stacul
The main purpose of this paper is the design, development and implementation of a PCM bit-synchronizer based on a System Generator and Simulink model. The entire system will be applied to a ground station with an ad-hoc telemetric data acquisition system to be applied in UAV monitoring and sounding rockets. Based on this information, the ground station will compute the platform trajectories, velocities and attitudes.
Volume: 9
Issue: 1
Page: 1-11
Publish at: 2020-03-01

Development of option c measurement and verification model using hybrid artificial neural network-cross validation technique to quantify saving

10.11591/ijai.v9.i1.pp25-32
Wan Nazirah Wan Md Adnan , Nofri Yenita Dahlan , Ismail Musirin
This paper aims to develop a hybrid artificial neural network for Option C Measurement and Verification model to predict monthly building energy consumption. In this work, baseline energy model development using artificial neural networks embedded with artificial bee colony optimization and cross validation technique for a small dataset were considered. Artificial bee colony optimization with coefficient of correlation fitness function was used in optimizing the neural network training process and selecting the optimal values of initial weights and biases. Working days, class days and cooling degree days were used as input meanwhile monthly electricity consumption as an output of artificial neural network. The results indicated that this hybrid artificial neural network model provided better prediction results compared to the other model. The best model with the highest value of coefficient of correlation was selected as the baseline model hence is used to determine the saving. 
Volume: 9
Issue: 1
Page: 25-32
Publish at: 2020-03-01

A compact graphene based nano-antenna for communication in nano-network

10.11591/ijres.v9.i1.pp12-18
M. Saravanan , V.R. Prakash
Due to recent advances in nanotechnology, the use of nano-devices and its network becomes more popular in the field of medical, commercial and military applications. One of the major issues in designing nano-network is miniaturization of nano-devices which are limited due to communication antenna used in that device and its power constraints. At 1000nm size, an antenna resonates at around 100 THz which suffers from greater propagation loss and provides signal coverage of micrometer distances. Hence there is a need for nano-antenna with reduced size and also operating at mid infrared frequencies to provide a good signal coverage. In this paper, graphene-based nano-antenna is presented. The model resonates at 55THz frequency with a peak gain of 5.47 dB in the propagation direction. The model exploits the principle of surface plasma polarition waves for miniaturization and achieves 50% size reduction when compared to conventional nano-antenna and best suitable for nano-network communications.
Volume: 9
Issue: 1
Page: 12-18
Publish at: 2020-03-01

Low power 11T adder comparator design

10.11591/ijres.v9.i1.pp28-33
C.M.R. Prabhu , Tan Wee Xin Wilson , T. Bhuvaneswari
Comparator is a basic arithmetic component in a digital system and adders are the basic block of processor unit, the performance of adder will improve the system performance. The proposed 11T adder comparator is consists of three main components, namely XOR, inverter, and MUX logic. The circuit is designed and implemented based on top-down approach with 11 transistors. The proposed cell can be used at higher temperature with minimal power loss. It also gives faster response for the carry output. The proposed comparator circuit shows 63.80% improvement in power consumption than other circuits.
Volume: 9
Issue: 1
Page: 28-33
Publish at: 2020-03-01

A novel approach to assess radial distribution system for optimal sizing of microgrid

10.11591/ijeecs.v17.i3.pp1618-1625
Shalaka Chaphekar , Anjali A. Dharme
The performance of Radial Distribution System (RDS) is enhanced by maintaining the appropriate Penetration Ratio (PR) of Distributed generation.  However, it has been observed that Penetration Ratio cannot be useful to analyze the impact of a Microgrid on performance of RDS. Hence a new index ‘Relief Factor’ (RF) is defined in this paper and the impact of Microgrid at different RF is studied. This paper presents an approach to compute daily energy losses variation when Microgrids of varying RF are connected to RDS having different maximum demands.  A methodology has been proposed for finding optimal RF and location of Microgrid.  In addition, the impact of maximum demand of RDS on optimum RF is analyzed. This paper gives the novel concept of assessing the RDS for integration of Microgrid based on maximum demand of RDS as well as Microgrid and sizing of Microgrid based on optimum Relief Factor.
Volume: 17
Issue: 3
Page: 1618-1625
Publish at: 2020-03-01

A computer vision-based weed control system for low-land rice precision farming

10.11591/ijaas.v9.i1.pp51-61
Olayemi Mikail Olaniyi , E. Daniya , J. G. Kolo , J. A. Bala , A. E. Olanrewaju
Agricultural sector is one of the economic pillars of developing nations, because it provides means of boosting gross domestic profit. However, weeds pose a threat to food crop by competing with it for nutrients and undermining the profit to be made from it. The treatment of these weeds is necessary, but at minimal impact on the actual food crop. Herbicide usage is one major means of weed control, owning to the expensive and labour-intensive nature of hand weeding. Recently, the need for site specific spraying has been on the rise because of health concerns which have been raised on the effect of herbicides on food crops and the effect on the environment. Most research on the field focuses on accurately identifying the weeds whilst neglecting the weed control. In this research, we apply fuzzy logic-based expert system to control how herbicide is sprayed on low-land rice in order to reduce excessive herbicide usage. The system supplies the control with weed density (Box size) and confidence level. The values of both are then passed to the fuzzy logic control for spray decision. The Sugeno as well as Mamdani models were tested using generated values for detected weed box size and confidence levels of the computer vision. The mean absolute error obtained was 0.9 for both, and 0.3 and 0.2 respectively, for the mean square error. The error shows how accurate the system can be and with low error value, it shows that the system implementation is capable of providing control for spraying of herbicides which in turn will yield more returns for low-land rice farmers.
Volume: 9
Issue: 1
Page: 51-61
Publish at: 2020-03-01

Internet data traffic analysis for identifying usage trends on each day of the week in a university

10.11591/ijeecs.v17.i3.pp1442-1452
Aderibigbe Adekitan , Claudius Awosope
Internet data traffic monitoring and management are important requirements for ensuring top notch quality of service in a network. Data traffic logs contain useful hidden information that can be harnessed and interpreted as a resource for making informed network management decisions. In this study, logged internet data traffic for both the upload and download traffic in a university for one year was analysed using statistics and partial least squares approach to structural equation modelling (PLS-SEM). Time series plots, statistical properties and trends for each day of the week over a 51-week period were developed. The result shows that the most data was downloaded on Thursdays while the most upload occurred on Mondays. A path model was developed using Smart PLS3, and the performance of the model was evaluated using the construct reliability and validity of the model. The results reveal that the weekly variance is majorly accounted for by usage variations on Tuesdays, Fridays and Saturdays. An overall model R-square value of 0.876 was observed.
Volume: 17
Issue: 3
Page: 1442-1452
Publish at: 2020-03-01

Application of optimal artificial intelligence based tuned controllers to a class of embedded nonlinear power system

10.11591/ijres.v9.i1.pp83-92
Magdy A. S. Aboelela
This paper studies the implementation of the Bat Inspired Algorithm (BIA) as an optimization technique to find the optimal parameters of two classes of controllers. The first is the classical Proportional-Integral-Derivative (PID). The second is the hybrid fractional order and Brain Emotional Intelligent controller. The two controllers have been implemented, separately, for the load frequency control of a single area electric power system with three physical imbedded nonlinearities. The first nonlinearity represents the generation’s rate constraint (GRC). The second is owing to the governor dead band (GDB). The last is due to the time delay imposed by the governor-turbine link, the thermodynamic process, and the communication channels. These nonlinearities have been embedded in the simulation model of the system under study. Matlab/Simulink software has been applied to obtain the results of applying the two classes of controllers which have been, optimally, tuned using the BIA. The Integral of Square Error (ISE) criterion has been selected as an element of the objective function along with the percentage overshoot and settling time for the optimum tuning technique of the two controllers. The simulation results show that when using the hybrid fractional order and Brain Emotional Intelligent controller, it gives better response and performance indices than the conventional Proportional-Integral-Derivative (PID) controllers.
Volume: 9
Issue: 1
Page: 83-92
Publish at: 2020-03-01

Optimization of parameters of neuro-fuzzy model

10.11591/ijeecs.v17.i3.pp1206-1209
Lyalya Bakievna Khuzyatova , Lenar Ajratovich Galiullin
The questions and problems of the formation of knowledge bases of intelligent man-machine decision support systems are considered. The neuron-fuzzy model used in the work is described. The need for increasing the efficiency of the neuron-fuzzy model in the formation of knowledge bases is being updated. The task is to develop methods and algorithms for presetting and optimizing the parameters of a fuzzy neural network. To solve difficult formalized tasks, it is necessary to develop decision support systems - expert systems based on a knowledge base. ES developers are constantly faced with the problems of “extraction” and formalization of knowledge, as well as the search for new ways to obtain it. To do this, use the extraction, acquisition and formation of knowledge. Currently, the formation of knowledge bases is relevant for the creation of hybrid technologies - fuzzy neural networks that combine the advantages of neural network models and fuzzy systems. The analysis of the efficiency of the fuzzy neural network carried out in the work showed that the quality of training of the NN largely depends on the choice of the number of fuzzy granules for input drugs. In addition, to use fuzzy information formalized by the mathematical apparatus of fuzzy logic, procedures are required for selecting optimal forms and presetting the parameters of the corresponding membership functions (MF).
Volume: 17
Issue: 3
Page: 1206-1209
Publish at: 2020-03-01

An improved ACS algorithm for data clustering

10.11591/ijeecs.v17.i3.pp1506-1515
Ayad Mohammed Jabbar , Ku Ruhana Ku-Mahamud , Rafid Sagban
Data clustering is a data mining technique that discovers hidden patterns by creating groups (clusters) of objects. Each object in every cluster exhibits sufficient similarity to its neighbourhood, whereas objects with insufficient similarity are found in other clusters. Data clustering techniques minimise intra-cluster similarity in each cluster and maximise inter-cluster dissimilarity amongst different clusters. Ant colony optimisation for clustering (ACOC) is a swarm algorithm inspired by the foraging behaviour of ants. This algorithm minimises deterministic imperfections in which clustering is considered an optimisation problem. However, ACOC suffers from high diversification in which the algorithm cannot search for best solutions in the local neighbourhood. To improve the ACOC, this study proposes a modified ACOC, called M-ACOC, which has a modification rate parameter that controls the convergence of the algorithm. Comparison of the performance of several common clustering algorithms using real-world datasets shows that the accuracy results of the proposed algorithm surpasses other algorithms. 
Volume: 17
Issue: 3
Page: 1506-1515
Publish at: 2020-03-01
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